This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Probabilistic Prediction and Validation of Vehicle Dynamic Performance by Concurrent Modeling Approach
Technical Paper
2016-01-0482
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
This paper presents the latest development of using an integrated modeling approach to estimate the statistical ranges of key vehicle dynamics performance in the early design phase. The virtual analytical tools predict the statistical confidence interval for specified ride and handling (R&H) metrics to enable a robust design by concurrently simulating the dimensional tolerance of the structural parts as well as the compliance variation. The compliance variation can be defined as load deflection properties of bushings as well as vehicle weight effects on preload. The model can then be used to better represent real world customer experience, allowing prediction of performance ranges relative to targets. In order to better predict these targets, measurements of physical vehicles were made and compared to the model to reveal the actual interactions relative to the theoretical.
Recommended Content
Technical Paper | Instantaneous and Statistical Structures of Non-Evaporative Diesel Spray |
Technical Paper | A Method for Simulation of GD&T Specifications |
Authors
Citation
Zhang, B., Robertson, J., and Whitehead, G., "Probabilistic Prediction and Validation of Vehicle Dynamic Performance by Concurrent Modeling Approach," SAE Technical Paper 2016-01-0482, 2016, https://doi.org/10.4271/2016-01-0482.Also In
References
- Zhang , B. , Robertson , J. , Whitehead , G. , and Pillutla , R. Combined Variation Modeling of Structural and Tuning Components for Vehicle Performance Assessment, SAE Int. J. Mater. Manf. 6 3 441 446 2013 10.4271/2013-01-0944
- Zhang , B. Applying Virtual Statistical Modeling for Vehicle Dynamics SAE Int. J. Mater. Manuf. 3 1 38 43 2010 10.4271/2010-01-0019
- Velden , A. , Kayupov , M. , Hortig , N. , and Naehring , D. Proceedings of NAFEMS 2013 World Congress The Probabilistic Certificate of Correctness Metric for Early Virtual Prototype Verification and Validation 01/2013
- ADAMS Software MSC Software Corporation Santa Ana, CA 92707, USA 2014
- iSight Software SIMULIA Providence, RI 02909, USA 2014
- DCS-3D Software Dimensional Control System Troy, Michigan, USA 2014
- Minitab Software Minitab Inc. State College, PA, USA 2014